A combinatorial optimization algorithm for multiple cloud service composition. (February 2015)

• Record Type: Journal Article
• Authors: Kurdi, Heba; Al-Anazi, Abeer; Campbell, Carlene; Al Faries, Auhood
• Is Part Of: Computers & electrical engineering. Volume 42(2015)
• Page Start: 107
• Page End: 113
• Publication Date: 2015-02
• Subjects: Combinational optimization -- Web services -- Service composition -- Cloud computing -- Multiple clouds -- Cross-clouds; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2014.11.002
• Languages: English
• ISSNs: 0045-7906

Abstract

Graphical abstract: Highlights: The COM2 algorithm efficiently considers multiple clouds while composing services. The proposed algorithm successfully competes with previous algorithms. Low examined service number is achieved without impacting the combined cloud number. Abstract: Service composition is an evolving approach that increases the number of applications of cloud computing by reusing existing services. However, the available methods focus on generating composite services from a single cloud, which limits the benefits that are derived from other clouds. This paper proposes a novel COMbinatorial optimization algorithm for cloud service COMposition (COM2) that can efficiently utilize multiple clouds. The proposed algorithm ensures that the cloud with the maximum number of services will always be selected before other clouds, which increases the possibility of fulfilling service requests with minimal overhead. The experimental results demonstrate that the COM2 successfully competes with previous multiple cloud service composition algorithms by examining a small number of services—which directly relates to execution time—without compromising the number of combined clouds.